Background
The purpose of this script is to predict genomic breeding values (GEBVs) using a conventional single time point (TP) gBLUP model. The TP model is \[\mathbf{y} = \mathbf{Xb} + \mathbf{Zu} + \mathbf{Qs} + \mathbf{e}\] where \(\mathbf{y}\) is PSA at each of the 20 days; \(\mathbf{Z}\) and \(\mathbf{Q}\) are incidence matrices corresponding to the random additive genetic effect (\(\mathbf{u}\)), and random experimental effect (\(\mathbf{s}\)), respectively; and \(\mathbf{e}\) is the random residual error. Here we assume the random terms are as follows \(\mathbf{u} \sim N(0, \mathbf{G}\sigma_g^2)\), \(\mathbf{s} \sim N(0, \mathbf{I}\sigma_s^2)\), and \(\mathbf{e} \sim N(0, \mathbf{I}\sigma_e^2)\). A genomic relationship matrix (\(\mathbf{G}\)) was calculated as described for the RR approach.
Fitting the TP model.
Here is the .as file for ASREML.
!RENAME !ARG Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 Y11 Y12 Y13 Y14 Y15 Y16 Y17 Y18 Y19 Y20
SINGLE TP
NID !A
Exp !A
Y1 !/100000
Y2 !/100000
Y3 !/100000
Y4 !/100000
Y5 !/100000
Y6 !/100000
Y7 !/100000
Y8 !/100000
Y9 !/100000
Y10 !/100000
Y11 !/100000
Y12 !/100000
Y13 !/100000
Y14 !/100000
Y15 !/100000
Y16 !/100000
Y17 !/100000
Y18 !/100000
Y19 !/100000
Y20 !/100000
G2.grm
PSA.cleaned.mn.csv !SKIP 1 !MAXITER 1000 !EXTRA 100 !WORKSPACE 6144 !SIGMAPAR !DOPART 1
!PATH 1
$1 ~ mu !r Exp grm(NID)Here is how it was run.